Anomaly detection algorithm based on fuzzy and immune theory in wireless sensor networks

作者：Fu Rong Rong^*; Zheng Kang Feng; You Fu Cheng; Zhang Dong Mei; Wu Bin; Yang Yi Xian

来源：Journal of Nanjing University of Science and Technology(Natural Science), 2012, 36(SUPPL.1): 137-142.

• Analysis and simulation
• Anomaly detection
• Anomaly-detection algorithms
• Artificial immune
• Constrained resources
• Detection performance
• Fuzzy inference systems
• Immune theory
• Linguistic variable
• Negative selection algorithm
• Self-distance
• V-Detector algorithm

In order to improve the anomaly detection performance for wireless sensor network, an anomaly detection algorithm based on fuzzy and immune theory is proposed. This algorithm improves classical negative selection algorithm and raises a fuzzy inference system to classify the samples within the holes. The fuzzy inference system uses two linguistic variables named self distance and detector distance as the inputs which solve the rule "dimension disaster" problem effectively. This advantage makes algorithm suitable for wireless sensor networks with constrained resource. Theoretical analysis and simulation results show that: compared with V-detector algorithm, the proposed algorithm improves the detection performance significantly and is more suitable for wireless sensor networks.

• 出版日期2012
• 单位北京交通大学